Scale and shape mixtures of multivariate skew-normal distributions

Reinaldo B. Arellano-Valle, Clécio S. Ferreira and Marc G. Genton

Journal of Multivariate Analysis, 2018, vol. 166, issue C, 98-110

Abstract: We introduce a broad and flexible class of multivariate distributions obtained by both scale and shape mixtures of multivariate skew-normal distributions. We present the probabilistic properties of this family of distributions in detail and lay down the theoretical foundations for subsequent inference with this model. In particular, we study linear transformations, marginal distributions, selection representations, stochastic representations and hierarchical representations. We also describe an EM-type algorithm for maximum likelihood estimation of the parameters of the model and demonstrate its implementation on a wind dataset. Our family of multivariate distributions unifies and extends many existing models of the literature that can be seen as submodels of our proposal.

Keywords: EM-algorithm; Scale mixtures of normal distributions; Scale mixtures of skew-normal distributions; Shape mixtures of skew-normal distributions; Skew-normal distribution; Skew scale mixtures of normal distributions (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (13)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:166:y:2018:i:c:p:98-110

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DOI: 10.1016/j.jmva.2018.02.007

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